Date of Award

Fall 2001

Document Type

Thesis

Degree Name

Master of Science in Biomedical Engineering - (M.S.)

Department

Biomedical Engineering Committee

First Advisor

Stanley S. Reisman

Second Advisor

Michael T. Bergen

Third Advisor

Tara L. Alvarez

Fourth Advisor

Richard J. Servatius

Abstract

The use of the Electroencephalogram (EEG) for diagnosis of brain related diseases is becoming a popular technique in the clinical and research environment. To achieve accurate reading of EEG, signal representation and classification becomes extremely important. The goal of this project was to develop a basic software program for acquiring and online processing of the electrical activity recorded from the brain. A program was developed using the LabVIEW programming software by National Instruments. Basic hardware components recorded the EEG signal and a software component divided the data into delta, theta, alpha and beta bands in the frequency domain. Emphasis was placed on critical programming parameters such as sampling rate, filtering, windowing and FFT.

The developed software was implemented in an already existing experimental paradigm that studies classical conditioning response. To prove the validity and accuracy of the system, a pilot experiment was conducted where EEG was recorded from six subjects. Data showed that as the subject learns, continuous theta activity is observed. Performance and testing of the EEG system demonstrated that the on line processing of EEG could be used in a variety of other applications where neural activity is involved such as classifying sleep stages in patients, discriminating various mental tasks, recording continuous EEG activity in neonatals with brain dysfunction etc.

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